def makecompletegraph(self): """ """ OrganismGraph.makecompletegraph(self) for u,v in self.weights.keys(): if not self._edge_binary_entropies.has_key((u,v)): self._edge_binary_entropies[(u,v)] = (1.0,1.0)
def __init__(self,tcode_5p_windowsize=201,tcode_3p_windowsize=201): """ Initialize a AlignedStartCodonGraph """ OrganismGraph.__init__(self) self._tcode5pscore = {} self._tcode3pscore = {} self._TCODE_5P_WINDOWSIZE = tcode_5p_windowsize self._TCODE_3P_WINDOWSIZE = tcode_3p_windowsize
def __init__(self,max_node_count=None,min_pssm_score=None,aligned_site_aa_offset=None): """ Initialize a AlignedPssmObjectGraph """ OrganismGraph.__init__(self) self._node_pssm = {} self._node_object = {} self.MIN_PSSM_SCORE = min_pssm_score self.MAX_NODE_COUNT = max_node_count self.ALIGNED_SITE_AA_OFFSET = aligned_site_aa_offset
def __init__(self): """ Initialize a GeneTreeGraph """ # Initialize as an OrganismGraph OrganismGraph.__init__(self) # self.weights contains identityscores # add similar dicts for aa_identity, bitscore_ratios and nt_identity self._aa_identity_percentages = {} self._bitscore_ratios = {} self._nt_identity_percentages = {}
def __init__(self): """ Initialize a PacbpCollectionGraph """ # Initialize as an OrganismGraph OrganismGraph.__init__(self) # set extra attributes self._node_object = {} self._node_pssm = {} # needed for backwards compatibilty with PacbpCollectionGraph, CodingBlockGraph self.pacbps = {} self._omsr = {}
def pairwisecrosscombinations_organism(self,order_by=None): """ Get unique cross combinations of organisms in the graph, ordered on request @rtype: list @return: list of all unique combinations of two organisms @attention: returns ORDERED list of ORDERED tuples of organism combinations @attention: orderability overwrites OrganismGraph.pairwisecrosscombinations_organism @attention: use order_by='identity' to obtain identity ordering except alphabetical """ if order_by == 'identity': combinations = [] for a in self.organism_set(): for b in self.organism_set(): if a == b: continue combi = [a,b] combi.sort() if combi == [a,b]: wt = self.weights[(a,b)] combinations.append( ( wt, tuple(combi) ) ) # return the ordered (by wt) list of unique combinations combinations.sort() combinations.reverse() return [ combi for (wt,combi) in combinations ] else: # return basal (alphabetical) ordered pairs of organisms return OrganismGraph.pairwisecrosscombinations_organism(self)
def pairwisecrosscombinations_organism(self, order_by=None): """ Get unique cross combinations of organisms in the graph, ordered on request @rtype: list @return: list of all unique combinations of two organisms @attention: returns ORDERED list of ORDERED tuples of organism combinations @attention: orderability overwrites OrganismGraph.pairwisecrosscombinations_organism @attention: use order_by='identity' to obtain identity ordering except alphabetical """ if order_by == 'identity': combinations = [] for a in self.organism_set(): for b in self.organism_set(): if a == b: continue combi = [a, b] combi.sort() if combi == [a, b]: wt = self.weights[(a, b)] combinations.append((wt, tuple(combi))) # return the ordered (by wt) list of unique combinations combinations.sort() combinations.reverse() return [combi for (wt, combi) in combinations] else: # return basal (alphabetical) ordered pairs of organisms return OrganismGraph.pairwisecrosscombinations_organism(self)
def __init__(self): """ Initialize a PssmObjectCollectionGraph; objects on orfs on pacbporfs (splice sites, start sites, stop sites) """ OrganismGraph.__init__(self) self._node_pssm = {} self._node_object = {} self.MIN_PSSM_SCORE = None # list to store aligned sites graphs self.alignedsites = [] # dictionary keeping track of considered range self._organism_consideredrange = {} # Attributes storing information for thresholds of # how this collection was generated self.ALIGNED_SITE_AA_OFFSET = None self.MIN_PSSM_SCORE = None
def __init__(self,cbg,tcode_5p_windowsize=201,tcode_3p_windowsize=201): """ Initialize a AlignedStopCodonGraph """ OrganismGraph.__init__(self) # attribute for storing the CBG itself self._codingblockgraph = cbg # attributes for TCODE data self._tcode5pscore = {} self._tcode3pscore = {} self._TCODE_5P_WINDOWSIZE = tcode_5p_windowsize self._TCODE_3P_WINDOWSIZE = tcode_3p_windowsize # is_optimal_xxx thresholds self._optimal_min_tcode = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_TCODE self._optimal_max_tcode = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_TCODE self._optimal_min_weight = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_WEIGHT self._optimal_max_weight = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_WEIGHT self._optimal_min_gtgweakest = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_GTGWEAKEST self._optimal_max_gtgweakest = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_GTGWEAKEST # run function codingblock_collectionharvesting.align_stop_codons # to fully initialize the object self = codingblock_collectionharvesting.align_stop_codons(cbg,self)
def __init__(self, cbg, tcode_5p_windowsize=201, tcode_3p_windowsize=201): """ Initialize a AlignedStopCodonGraph """ OrganismGraph.__init__(self) # attribute for storing the CBG itself self._codingblockgraph = cbg # attributes for TCODE data self._tcode5pscore = {} self._tcode3pscore = {} self._TCODE_5P_WINDOWSIZE = tcode_5p_windowsize self._TCODE_3P_WINDOWSIZE = tcode_3p_windowsize # is_optimal_xxx thresholds self._optimal_min_tcode = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_TCODE self._optimal_max_tcode = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_TCODE self._optimal_min_weight = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_WEIGHT self._optimal_max_weight = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_WEIGHT self._optimal_min_gtgweakest = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MIN_GTGWEAKEST self._optimal_max_gtgweakest = ALIGNEDSTOPCODONGRAPH_OPTIMALITY_MAX_GTGWEAKEST # run function codingblock_collectionharvesting.align_stop_codons # to fully initialize the object self = codingblock_collectionharvesting.align_stop_codons(cbg, self)
def add_edge(self, u, v, wt=1, entropy=1.0): """ """ OrganismGraph.add_edge(self,u,v,wt=wt) self._edge_binary_entropies[(u,v)] = (entropy,entropy) self._edge_binary_entropies[(v,u)] = (entropy,entropy)